US7995641B2 - Method and apparatus for code power parameter estimation for received signal processing - Google Patents
Method and apparatus for code power parameter estimation for received signal processing Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/69—Spread spectrum techniques
- H04B1/707—Spread spectrum techniques using direct sequence modulation
- H04B1/7097—Interference-related aspects
- H04B1/7103—Interference-related aspects the interference being multiple access interference
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/69—Spread spectrum techniques
- H04B1/707—Spread spectrum techniques using direct sequence modulation
- H04B1/7097—Interference-related aspects
- H04B1/711—Interference-related aspects the interference being multi-path interference
- H04B1/7115—Constructive combining of multi-path signals, i.e. RAKE receivers
- H04B1/712—Weighting of fingers for combining, e.g. amplitude control or phase rotation using an inner loop
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B2201/00—Indexing scheme relating to details of transmission systems not covered by a single group of H04B3/00 - H04B13/00
- H04B2201/69—Orthogonal indexing scheme relating to spread spectrum techniques in general
- H04B2201/707—Orthogonal indexing scheme relating to spread spectrum techniques in general relating to direct sequence modulation
- H04B2201/7097—Direct sequence modulation interference
- H04B2201/709727—GRAKE type RAKE receivers
Definitions
- the present invention generally relates to communication networks, such as wireless communication networks, and particularly relates to estimation of channelization code powers for received signal processing.
- a received signal represents a composite of individually coded signals.
- a given individual signal of interest is recovered at the receiver by correlating the received composite signal with the individual signal's spreading code.
- spreading codes are taken from an orthogonal set of spreading codes, e.g., length-16, length-32, or length-64 Walsh codes.
- orthogonal spreading codes enables the receiver to recover an individual signal of interest from the composite signal that is free from interference caused by the other signals encoded within the composite signal.
- real-world signal reception and despreading are compromised by a range of signal impairments, including various forms of interference.
- transmissions from adjacent transmitters may use the same spreading codes and therefore interfere with one another. Similar reuse problems arise in Multiple-Input-Multiple-Output (MIMO) transmission scenarios, where channelization code reuse across transmit antennas may be used.
- MIMO Multiple-Input-Multiple-Output
- the use of non-orthogonal (long) scrambling codes between transmitters in wireless communication networks represents an additional source of interference that compromises despreading performance.
- Estimating code cross-correlations therefore represents a useful aspect of interference estimation and suppression in CDMA receivers.
- estimating the power allocations for channelization codes represents one aspect of determining code correlations. Details relating to certain aspects of code power estimation associated with correlation estimation processing appear in the commonly owned U.S. Pat. No. 7,590,167, which issued on 15 Sep. 2009. The '167 patent is entitled, “A Method and Apparatus for QAM Demodulation in a Generalized RAKE Receiver,” and was filed on 30 Aug. 2005 and assigned application Ser. No. 11/215,584. The '167 patent presents certain aspects of code power estimation as part of “Generalized Rake” (G-Rake) receiver processing, where a correlation fitting procedure was used to estimate code powers.
- G-Rake Generalized Rake
- LMUD Linear Multi-User-Detection
- channelization code power estimates are generated for a number of data channels in a received CDMA signal based on a joint determination process.
- Application of joint processing in this context yields improved, e.g., lower-noise and/or more accurate, estimation of data channel code powers and corresponding estimations of noise variance. These improvements arise from exploitation of joint processing of measured data value correlations across two or more data channel codes represented in the received signal.
- a method of estimating channelization code powers for a received CDMA signal comprises despreading the received CDMA signal using one or more channelization codes used for data signals in the received CDMA signal to obtain despread data values for each of the one or more channelization codes, measuring correlations between the despread data values for each of the one or more channelization codes, and jointly determining channelization code power estimates for at least two channelization codes used in the received CDMA signal based on the measured correlations.
- measuring correlations between the despread data values for each of the one or more channelization codes comprises determining matrices of data correlations for each of a plurality of data channel codes over one or more time slots.
- jointly determining channelization code power estimates for at least two channelization codes used in the received CDMA signal based on the measured correlations comprises jointly fitting the matrices of data correlations in a least squares estimation process to determine code power estimates corresponding to the plurality of data channel codes.
- jointly determining channelization code power estimates for at least two channelization codes used in the received CDMA signal based on the measured correlations comprises forming a weighted average from the measured correlations determined for two or more channelization codes, and determining the channelization code power estimates based at least in part on the weighted average.
- the method may further comprise determining weights for forming the weighted average based on knowledge of relative channelization code power allocations for the two or more channelization codes.
- a base station e.g., a Wideband CDMA base station
- uplink processing is advantageous in improving interference suppression in the detection of data transmissions from high-speed users on the uplink.
- joint determination of data channel code powers may be implemented at a wireless communication device, e.g., a mobile station in a wireless communication network, and applied to downlink processing.
- processing is advantageous in improving interference suppression in the detection of data transmissions for HSDPA or other high-speed data services.
- FIG. 1 is a block diagram of a wireless communication network including an embodiment of a base station for supporting communications with a wireless communication device, where one or both the base station and wireless communication device are configured for estimation of channelization code powers via joint determination processing as taught herein.
- FIG. 2 is a block diagram of one embodiment of a communication receiver, or at least a portion thereof, such as may be implemented, for example, in the wireless communication device and/or base station of FIG. 1 for joint determination of channelization code powers.
- FIG. 3 is a logic flow diagram for one embodiment of joint determination of channelization code powers.
- FIG. 4 is a table of scaling factors useful in one or more method embodiments of determining channelization code powers.
- FIG. 5 is a block diagram of another embodiment of a communication receiver, or at least a portion thereof, such as may be implemented, for example, in the wireless communication device and/or base station of FIG. 1 for joint determination of channelization code powers.
- FIG. 6 is a logic flow diagram for another embodiment of joint determination of channelization code powers.
- FIG. 1 presents a simplified illustration of one embodiment of a wireless communication network 10 , that includes a base station 12 configured to support downlink and uplink communications with a plurality of wireless communication devices 14 , with just one such base station and device shown for simplicity.
- the base station 12 and the wireless communication device 14 are configured to support relatively high-rate data communication, such as High Speed Downlink Packet Access (HSDPA) downlink services and/or High Speed Uplink Packet Access (HSUPA) uplink services according to the Wideband Code Division Multiple Access (WCDMA) standard.
- HSPA high speed packet access
- HSPA high speed packet access
- the base station 12 includes a code power estimation circuit 16 for estimating the allocations of transmission power to the codes represented in the composite uplink signals it receives.
- the wireless communication device 14 includes a code power estimation circuit 18 , which may be implemented as part of a receiver 20 included in the wireless communication device 14 .
- code power estimation as taught herein can be applied to uplink received signal processing and/or to downlink received signal processing, with the code power estimation circuit 16 being one non-limiting example of the former application, and the code power estimation circuit 18 being one non-limiting example of the latter application.
- operation of the code power estimation circuit 16 may be tailored for uplink signals while operation of the estimation circuit 18 may be tailored for downlink signals.
- either circuit is configured to produce estimates of channelization code powers for two or more channelization codes represented in a received CDMA signal.
- code power estimates may be expressed as code power scale factors, where each scale factor relates the relative power allocation of the corresponding data code to a pilot code power.
- Estimated channelization code powers held in working memory after their determination are useful, for example, in interference suppression and other received signal processing operations.
- the code power estimation circuit 16 if included in the base station 12 , the code power estimation circuit 16 generates code power estimates for channelization codes used in a CDMA signal received on the uplink, and, if included in the wireless communication device 14 , the code power estimation circuit 18 generates code power estimates for channelization codes used in a CDMA signal received on the downlink.
- the base station 12 includes interface/control circuits 22 , which provide overall communication and operational control, as well as interfacing to other network entities for the transfer of user data to/from targeted ones of the wireless communication devices 14 , and various control and signaling information.
- Transceiver circuits 24 including signal processing and radiofrequency (RF) transmit/receive circuits, process user data (traffic) and control signals for transmission by spreading the individual signals using orthogonal and/or quasi-orthogonal spreading codes within a defined code tree, e.g., a set of Walsh codes.
- the resulting composite CDMA signal(s) are transmitted from one or more antennas 26 on the downlink, e.g., Multiple-Input-Multiple-Output (MIMO) transmission may be used.
- MIMO Multiple-Input-Multiple-Output
- the code power estimation circuit 16 may be used to perform code power estimation for uplink CDMA signals received from the wireless communication device 14 .
- the wireless communication device 14 which may be a cellular radiotelephone, pager, PDA, computer, modem or other network access card, etc., includes a wireless receiver 20 , which processes the CDMA signals received from the base station 12 on its one or more antennas 28 .
- the estimation circuit 18 if implemented at the wireless communication device 14 , therefore may be used to estimate channelization code powers for these downlink CDMA signals.
- the receiver 20 comprises a Linear Multi-User Detection (LMUD) receiver.
- LMUD Linear Multi-User Detection
- the receiver 20 is configured such that the multi-user detection processing represents a second processing stage, preceded by Rake processing wherein the received signal is Rake processed to produce Rake-combined (despread) values. These Rake combined values are processed over multiple channelization codes and symbol periods in an LMUD process to produce received symbol estimates.
- LMUD Linear Multi-User Detection
- the elements of R are the cross-correlations of the effective spreading waveforms of the symbols in s with themselves.
- the element relating Z n 0 with S n 1 is given by
- R ⁇ ( n 0 , n 1 ) ⁇ - ⁇ ⁇ ⁇ f n 0 H ⁇ ( t ) ⁇ f n 1 ⁇ ( t ) ⁇ d t , Eq . ⁇ ( 2 )
- Q is the number of receive antennas.
- the effective waveform considered is a combination of transmit waveform, radio channel impulse response, and receive filtering which includes receive chip filtering, despreading, and Rake combining. It can be shown that NOR is the covariance matrix of the noise vector n, where N 0 is the noise variance at the input of the Rake receiver circuitry implemented within the receiver 20 .
- MMSE Minimum Mean Square Error
- the above LMUD processing depends directly on the matrix A and the noise variance N 0 .
- the diagonal elements of A 2 represent the code powers of the symbols transmitted by the base station 12 .
- These code powers as well as the noise variance generally are unknown by the wireless communication device 14 , so they must be estimated. The estimation of these unknown parameters may be advantageously performed by the code power estimation circuit 18 .
- R 1 ( ⁇ tilde over (g) ⁇ ) is the intra-cell interference due to radio (medium) channel g scaled by the square-root of the per-symbol pilot channel energy E p
- R n captures the effect of white noise passing through the receive filter
- x ( A H A ) ⁇ 1 A H b.
- the matrix ⁇ circumflex over (R) ⁇ u can be used for obtaining G-Rake combining weights, and the code power estimate ⁇ circumflex over ( ⁇ ) ⁇ can be used as the data-to-pilot power ratio for decoding purposes.
- joint estimation as applied herein to the estimation of channel code powers provides multiple N 0 estimates that can be averaged to obtain a better overall estimate of N 0 .
- joint estimation provides a more complete system model that leads to a joint solution for the diagonal elements of A 2 and N 0 . This more comprehensive joint solution improves estimation accuracy for both A 2 and N 0 .
- the approaches taught herein directly encompass multiple base stations 12 .
- ⁇ tilde over (R) ⁇ indicates that the waveform correlation matrix is a function of the pilot channel power used for estimating channel coefficients. Therefore, the pilot channel power factor must be absorbed by the code power term in order to keep the overall result consistent. Taking the pilot scaling into account, one can write the diagonal elements of ⁇ 2 as either
- a ⁇ k 2 ⁇ k j K , Eq . ⁇ ( 11 ) depending upon the convention adopted by the receiver 20 (e.g., whether ⁇ k j is related to individual code power or to the sum power of a group of K codes). In either instance, the value of ⁇ k 2 is seen to be equal to or proportionate to the code power estimate ⁇ k j which as noted before expresses the code power estimate for the k th code as a power scale factor relative to pilot code power.
- E p j represents the pilot symbol energy for the j th base station
- E d,k j is the data symbol energy for code k (out of K codes) for the j th base station
- ⁇ k j represents the data-to-pilot symbol power ratio for the k th code of the j th base station. That is, ⁇ k j is a channelization code power estimate for the k th code of the j th base station, expressed in relation to the power of the pilot.
- the data correlation matrix for the k th code of base station j can be written as
- R I ( ⁇ tilde over (g) ⁇ q ) is an interference matrix that depends upon whether the interference is own-cell or other-cell;
- R n is a matrix that captures the effect of the receive filter implemented in receiver 20 on white noise;
- N 0 represents the power of the white noise passing through the receive filter;
- ⁇ tilde over (h) ⁇ j is a vector of net channel coefficients scaled by the pilot channel amplitude corresponding to the overall channel between the j th base station 12 and the wireless communication device 14 that includes the contribution of transmit filtering at the j th base station 12 , the radio channel, and the receive filter.
- Correlation fitting requires a measurement of R d,k j so that Eq. (12) may be used to formulate a least squares problem. Assuming slot-based processing, an estimate of the data correlation matrix for despread data values on the k th code may be formed as,
- the code power estimation circuit 18 in the receiver 20 can be configured to implement Eq. (14) to construct one or more least squares problems to solve for the unknown parameters (i.e. [ ⁇ 0 , ⁇ 1 , . . .
- the wireless communication device 14 is configured as a WCDMA terminal compatible with the HSPA mode of WCDMA.
- the HSPA mode involves allocating a (scheduled) user K-D spreading codes.
- Supporting LMUD processing in this context requires the receiver 20 to estimate which codes are active—i.e., which codes in the set of spreading codes are being used for the HSPA services—and calculate the corresponding code powers, e.g., expressed as power scale factors, and the noise variance.
- the receiver 20 can compute all the power scale factors and corresponding noise variance.
- K scale factors are estimated.
- Eq. (14) generally leads to a J+2 dimensional least squares problem
- the receiver 20 may be configured to model the J ⁇ 1 other cells (downlink) as white noise. Similar simplifications may be adopted at the base station 12 , where code power estimation for the uplink can be simplified by, for a given high-speed user of interest, modeling other high-speed users as white noise.
- processing at the wireless communication device 14 may assume that the 0 th wireless network cell (or user) is the serving cell (or user of interest).
- the joint estimation of code powers exploits knowledge of the relation between at least some of the channelization code powers of interest. For example, it may be known that a certain subset of channelization codes are all allocated the same power. More generally, the relative power allocations for two or more channelization codes may be known. Thus, the code power estimate for one code may be determined by knowing the code power for another code and the relative power relationship.
- FIG. 2 provides example details, set in the context of the code power estimation circuit 18 of receiver 20 in the wireless communication device 14 .
- the illustrated processing circuits operate on downlink received signals, but it should be understood that similar circuitry can be implemented as part of or in association with the code power estimation circuit 16 of the base station 12 .
- FIG. 2 and variations of the illustrated processing architecture may be implemented in hardware, software, or any combination thereof.
- the wireless communication device 14 is configured as a WCDMA-based communications terminal supporting HSPA services, where the wireless communication device is a high-speed data user that is allocated on a scheduled basis some or all of the set of spreading codes dedicated for high-speed services.
- the “RECV'D DATA” signal incoming from the left represents digitized samples of a received composite CDMA signal having multiple channelization code signals within it.
- Received signal samples are provided to pilot channel correlators 30 , e.g., Common Pilot Channel (CPICH) correlators, which generate despread pilot channel values.
- CPICH Common Pilot Channel
- a channel estimator 32 generates propagation channel estimates from the despread pilot channel values.
- Those channel estimates are then used by a structured element estimator 34 to generate estimates of the structured elements used to model received signal impairments, including an interference covariance matrix R I , a noise covariance matrix R n , and a net channel outer product term ⁇ tilde over (h) ⁇ tilde over (h) ⁇ H .
- a circuit block 35 includes sets of correlators 36 , outer product calculators 38 , and outer product averaging circuits 40 , for each channelization code assigned to the wireless communication device 14 for HSPA services (CODE 0 through CODE K ⁇ D ⁇ 1).
- the circuit block 35 further includes an averaging circuit 42 , which is configured to jointly determine the data correlation estimation matrix ⁇ circumflex over (R) ⁇ d using the per-code correlation estimates for high-speed service codes 0 through K ⁇ D ⁇ 1, as provided by the outer product averaging circuits 40 .
- a least squares error (LSE) estimator 44 performs a least squares fitting using the jointly determined ⁇ circumflex over (R) ⁇ d matrix.
- the LSE estimator 44 generates as its output the values ⁇ high-speed 2 and ⁇ circumflex over (N) ⁇ 0,high-speed , for the spreading codes allocated to the high-speed services.
- Another circuit block 45 includes circuitry to handle code power estimation for any spreading codes left in the composite signal for which the receiver 20 does not know the power allocations or relative power relationships.
- code power may be estimated for specific spreading codes or for a given level of a code tree such that the code power estimate for a given code branch represents code power allocated at that branch level, or a total of code power allocations made below that branch level for that given branch.
- code power may be estimated for a length-16 Walsh code, or may be estimated for a length-16 branch in a Walsh code tree, from which multiple longer-length child codes are derived, e.g., two length-32, four length-64, or so on.
- the circuit block 45 includes sets of correlators 46 , outer product calculators 48 , outer product averaging circuits 50 , and corresponding LSE estimators 52 . These circuits operate as above, but for the remaining codes not used for high-speed services.
- the outputs from the LSE estimator 44 , and the LSE estimators 52 operate as inputs to an estimation circuit 54 , which generates an average estimate of ⁇ circumflex over (N) ⁇ 0 . This average estimate represents an improved, lower-noise estimate than the single-shot estimates generated in conventional approaches.
- FIG. 3 illustrates a WCDMA/HSPA processing method for a single cell scenario.
- FIG. 3 could represent a scenario with one serving cell and the interference from other cells modeled as white noise.
- the illustrated processing begins with partitioning the channelization codes represented in the received signal into two sets: those assigned to high-speed service (set S d ) and those not assigned to the high-speed service (set S r ) (Step 100 ).
- the method includes forming R I ( ⁇ tilde over (g) ⁇ 0 ) and R n as described above—see, e.g., the description accompanying and computing ⁇ tilde over (h) ⁇ 0 via
- Step 104 processing continues with the estimation of the data correlation matrix ⁇ circumflex over (R) ⁇ d,k 0 using Eq. (13) for the k th code in S d (Step 108 ).
- R ⁇ d 1 K - D ⁇ ⁇ m ⁇ S d ⁇ R ⁇ d , m 0 (Step 114 ) for formulation of a least squares problem exemplified in Eq. (14), but with ⁇ circumflex over (R) ⁇ d used in place of ⁇ circumflex over (R) ⁇ d,k 0 (Step 116 ).
- the LSE solution yields the channel code powers ⁇ high-speed for all codes in set S d and yields the corresponding noise variance ⁇ circumflex over (N) ⁇ 0,high-speed
- the code power estimation circuit 18 may be configured to divide ⁇ high-speed by K (not shown in the method flow diagram). Also, the code power estimation circuit 18 may be configured to obtain ⁇ circumflex over (N) ⁇ 0 via
- a method of code power estimation based on joint processing includes jointly determining channelization code power estimates for at least two channelization codes used in a received CDMA signal based on the measured correlations. More particularly, joint determination comprises forming a weighted average from the measured correlations determined for two or more channelization codes, and determining the channelization code power estimates based at least in part on the weighted average. In at least one such embodiment, the method further comprises determining weights for forming the weighted average based on knowledge of relative channelization code power allocations for the two or more channelization codes.
- the receiver at the base station 12 or wireless communication device 14 may have knowledge of the relative power allocations for two or more data channel codes of interest, and may use such knowledge to determine one data channel code power as a function of another one, or may determine a common power scale factor, and then use that common power scale factor along with knowledge of code power allocation relationships to determine individual data code powers for one or more data channels of interest in the received signal.
- a WCDMA uplink signal for example, includes control channels, such as the DPCCH (Dedicated Physical Control Channel), HS-DPCCH (High-Speed Dedicated Physical Control Channel), and E-DPCCH (Enhanced Dedicated Physical Control Channel), and data channels, such as DPDCH (Dedicated Physical Data Channel) and E-DPDCH (Enhanced Dedicated Physical Data Channel).
- control channels such as the DPCCH (Dedicated Physical Control Channel), HS-DPCCH (High-Speed Dedicated Physical Control Channel), and E-DPCCH (Enhanced Dedicated Physical Control Channel)
- data channels such as DPDCH (Dedicated Physical Data Channel) and E-DPDCH (Enhanced Dedicated Physical Data Channel).
- the relative amplitude scaling for these channels is signaled or can be derived once the base station 12 knows the transport format used by the wireless communication device 14 .
- the relative amplitudes for DPCCH, HS-DPCCH, and E-DPCCH are signaled.
- the relative amplitudes for the data channel(s) can be derived, e.g., by the code power estimation circuit 16 , once the transport format is known.
- a data channel is configured to support a transport format combination set (TFCS) consisting of a number of transport format combinations (TFCs).
- TFCS transport format combination set
- An example TFCS is given in the table illustrated in FIG. 4 . There are three TFCs in this TFCS. Each TFC is associated with a spreading factor, a number of data codes used, and a relative code amplitude for each data code.
- any of these TFCs may be used.
- the wireless communication device 14 signals the TFC in use through control signaling, namely through use of a TFC indicator (TFCI).
- TFCI TFC indicator
- the base station 12 knows the relative code amplitudes in the data (code) branches.
- the control channels (DPCCH, HS-DPCCH, E-DPCCH) occupy a different code branch from the data branches.
- P the total power of the control branch is given by P( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), where P is constantly adjusted by power control.
- the code powers for the eight code branches are (P( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), P ⁇ 1 2 , 0, 0, 0, 0, 0, 0).
- the code powers for the four code branches are (P( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), P ⁇ 2 2 , 0, 0).
- the code powers for the 4 code branches are (P( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), P ⁇ 3 2 , P ⁇ 3 2 , 0).
- the code powers are mutually related via the amplitude scaling factors, i.e., the ⁇ values.
- these code power values can be translated to the ⁇ values as follows: for TFC 1 , ( ⁇ ( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), ⁇ 1 2 , 0, 0, 0, 0, 0, 0); for TFC 2 , ( ⁇ ( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), ⁇ 2 2 , 0, 0); and for TFC 3 , ( ⁇ ( ⁇ c 2 + ⁇ hs 2 + ⁇ ec 2 ), ⁇ 3 2 , ⁇ 3 2 , 0).
- ⁇ is a scaling factor common to all code branches.
- the code powers can be estimated as follows: estimate the ⁇ values for each code, and use those results to obtain an estimate of the ⁇ value from each code's ⁇ k j estimate; average all the K estimates to obtain a final estimate of ⁇ circumflex over ( ⁇ ) ⁇ .
- the code power estimation circuit 16 thus may be configured to obtain final estimates of ⁇ k j based on the ⁇ values and the final estimate of ⁇ circumflex over ( ⁇ ) ⁇ .
- the procedure described in FIG. 3 for downlink signal processing can be used.
- the base station 12 still can use the knowledge of the relative power to formulate a weighted average of data correlation:
- R ⁇ d ⁇ m ⁇ w m ⁇ R ⁇ d , m 0 ⁇ m ⁇ w m , Eq . ⁇ ( 15 )
- the weighting factor for code branch k can be proportional to the relative power scaling factor.
- the joint estimation processing taught herein for determining channelization code power estimates broadly comprises despreading a received CDMA signal using one or more channelization codes used for data signals in the received CDMA signal to obtain despread data values for each of the one or more channelization codes—e.g., despread data values (symbols) are generated via despreading (correlation) processing for one or more data channels in the received signal. Processing further includes measuring correlations between the despread data values for each of the one or more channelization codes.
- despreading the received CDMA signal comprises, for each of one or more channelization codes, obtaining despread data values for each of two or more correlation processing delays.
- a correlation processing delay represents the delay position of the correlator(s) used to obtain a particular stream of despread data values from the received (composite) signal.
- One or more such delays may be aligned with, for example, at least some of the propagation path delays determined for the received signal.
- a first correlator produces despread data values at a first processing delay and a second correlator produces despread data values for the same data channel but at a different processing delay.
- measuring correlations between the despread data values associated with each of the one or more channelization codes comprises, for each of the one or more channelization codes, determining cross-correlations of the despread data values between the two or more correlation processing delays, e.g., cross-correlating despread data samples taken at a given processing delay with corresponding despread data samples taken for the same data channel at the same or a different processing delay. Samples at any given delay may be cross-correlated with corresponding samples taken at any number of other delays.
- the method broadly continues with jointly determining channelization code power estimates for at least two channelization codes used in the received CDMA signal based on the measured correlations.
- joint parameter estimation exploits the fact that
- the code power estimation circuit 16 can be configured to ignore the common scaling factor for the codes of the high-speed data user, estimate J+K parameters, then average the K ⁇ D results that correspond to the high-speed user.
- this approach may not be preferred because the error in parameter estimation is directly related to the number of parameters estimated.
- FIG. 5 illustrates one embodiment of a functional circuit arrangement that may be implemented at the base station 12 , for example, for carrying out such processing.
- FIG. 5 describes a single user/cell scenario, or a scenario where the interference from other users/cells is modeled as white noise.
- FIG. 5 may note that many or most of the same circuit elements introduced and described in the context of FIG. 2 appear in FIG. 5 .
- FIG. 5 may note that many or most of the same circuit elements introduced and described in the context of FIG. 2 appear in FIG. 5 . However, FIG.
- the LSE estimator 60 is configured to perform least squares fitting based on considering all of R d,0 through ⁇ circumflex over (R) ⁇ d,K-D-1 and ⁇ circumflex over (R) ⁇ d,K-D through ⁇ circumflex over (R) ⁇ d,K-1 together in the LSE process.
- FIG. 6 illustrates processing that can be supported via the circuitry shown in FIG. 5 , and begins with forming R I ( ⁇ tilde over (g) ⁇ 0 ) and R n , and computing ⁇ tilde over (h) ⁇ 0 (e.g., via
- Step 124 and 126 are repeated for the next code. If so, processing continues with concatenation of K least squares problems into a joint least squares problem (Step 132 ), such as
- the ⁇ k j values may be related in terms of their relative power allocations through the ⁇ values and it suffices to estimate a common scaling factor ⁇ .
- ⁇ k 0 is known once the TFCI is decoded at the base station 12 .
- the base station 12 still knows that some of the code branches will always have zero code power. In this case, the ⁇ k j 's for these code branches can be set to zero. Doing so advantageously reduces the number of variables that need to be estimated.
- the joint determination of channelization code powers relies on measuring data channel code correlations by determining matrices of data correlations for each of a plurality of data channel codes over one or more time slots.
- jointly determining channelization code power estimates for at least two channelization codes used in the received CDMA signal comprises jointly fitting the matrices of data correlations in an LSE estimation process to determine code power estimates corresponding to the plurality of data channel codes.
- processing includes determining a common scaling factor for the plurality of data channel codes and determining the code power estimates as a function of the common scaling factor and known code power relationships.
- a communication receiver can be configured to estimate channelization code powers for a received CDMA signal.
- the communication receiver 20 (and more particularly, the included code power estimation circuit 18 ) represent a non-limiting example of an appropriately configured communication receiver.
- the communication receiver in one or more embodiments comprises one or more processing circuits configured to despread a received CDMA signal using one or more channelization codes used for data signals in the received CDMA signal to obtain despread data values for each of the one or more channelization codes.
- the processing circuit(s) are further configured to measure correlations between the despread data values for each of the one or more channelization codes, and jointly determine channelization code power estimates for at least two channelization codes used in the received CDMA signal based on the measured correlations.
- the one or more processing circuits may comprise correlators (e.g., correlators 36 and 46 ) to obtain despread data values, correlation measurement circuits (e.g., circuits 38 / 40 and 48 / 50 ) to obtain the measured correlations, and one or more LSE estimation circuits (e.g., LSE estimators 44 and 52 in FIG. 2 , and LSE estimator 60 in FIG. 5 ) to determine the channelization code power estimates as a function of the measured correlations.
- the correlation measurement circuits include a joint processing circuit (e.g., the weighted averaging circuit 42 in FIG.
- one or more least squares error (LSE) estimation circuits are configured to determine the channelization code power estimates in a joint fitting process that includes the measured correlations for a plurality of data channel codes.
- LSE estimator 60 in FIG. 5 one sees that the joint fitting process involves a plurality of data correlation matrices determined from the despread data values obtained for a plurality of data channel codes in the received signal.
- data correlation matrices are determined for each in a plurality of two or more data channel codes in the received signal, and these matrices are jointly fitted in a least squares estimation process to determine code power estimates corresponding to the plurality of data channel codes.
- processing may include determining a common scaling factor for the plurality of data channel codes and determining the code power estimates as a function of the common scaling factor and known code power relationships.
Abstract
Description
z=RAs+n Eq. (1)
where s=(s0, s1, . . . , SK′-1)T is a vector of received symbols to be considered for joint detection, and A=diag(A0, A1, . . . , AK′-1)T is a diagonal matrix with the kth element corresponding to the received amplitude for Sk. The elements of R are the cross-correlations of the effective spreading waveforms of the symbols in s with themselves. The element relating Zn
where fn(t)=[fn,0(t), fn,1(t), . . . , fn,Q-1(t)]T is the effective waveform for symbol n, with each element corresponding to each receive antenna q. Here, Q is the number of receive antennas. The effective waveform considered is a combination of transmit waveform, radio channel impulse response, and receive filtering which includes receive chip filtering, despreading, and Rake combining. It can be shown that NOR is the covariance matrix of the noise vector n, where N0 is the noise variance at the input of the Rake receiver circuitry implemented within the
ŝMMSE=AM−1z, Eq. (3)
where the matrix M is given by
M=RA 2 +N 0 I. Eq. (4)
LMUD processing may employ “sliding window” techniques, where the symbols for K users are jointly detected over 2N+1 symbol periods (K′=(2N+1)K). The “middle” K symbols (or a subset thereof) are of interest to the
{circumflex over (R)} d ≈αR 1({tilde over (g)})+N 0 R n +γ{tilde over (h)}{tilde over (h)} H. Eq. (1)
Ax=b, Eq. (2)
where
and vec(Q) denotes the operation of stacking the columns of matrix Q into a vector. With these definitions, the least squares estimate for the receiver parameters is given by
x=(A H A)−1 A H b. Eq. (4)
M={tilde over (R)}Ã 2+σ2 I. Eq. (9)
Here, {tilde over (R)} indicates that the waveform correlation matrix is a function of the pilot channel power used for estimating channel coefficients. Therefore, the pilot channel power factor must be absorbed by the code power term in order to keep the overall result consistent. Taking the pilot scaling into account, one can write the diagonal elements of Ã2 as either
depending upon the convention adopted by the receiver 20 (e.g., whether γk j is related to individual code power or to the sum power of a group of K codes). In either instance, the value of Ãk 2 is seen to be equal to or proportionate to the code power estimate γk j which as noted before expresses the code power estimate for the kth code as a power scale factor relative to pilot code power.
In Eq. (12), αq is the total energy per chip of base station q divided by per-symbol energy of the pilot for base station q (i.e. αq=Ec q/Ep q); {tilde over (g)}q is a vector of medium (i.e. radio) channel coefficients between base station q and the
where, xk j (m) is a vector of despread data values from the jth base station for the kth code during the mth symbol time and SF is the spreading factor of the data channel defined by the kth channelization code. Taking the measurement of Rd,k j from Eq. (13) and substituting into Eq. (12) yields the following expression,
where ≈ denotes approximately equal. The code
or other channel estimation technique (Step 104). Then, after initializing the code index k=0 (Step 106), processing continues with the estimation of the data correlation matrix {circumflex over (R)}d,k 0 using Eq. (13) for the kth code in Sd (Step 108). The index is then incremented, i.e., k=k+1 (Step 110). If k equals K−D (Step 112), the index-based incrementing stops. Otherwise, these processing steps are repeated for the next kth code.
(Step 114) for formulation of a least squares problem exemplified in Eq. (14), but with {circumflex over (R)}d used in place of {circumflex over (R)}d,k 0 (Step 116). The LSE solution yields the channel code powers γhigh-speed for all codes in set Sd and yields the corresponding noise variance {circumflex over (N)}0,high-speed As an optional processing step, the code
(e.g., a weighted average).
where the weighting factor for code branch k can be proportional to the relative power scaling factor. Further, even if the
Using Eq. (16) and assuming a
One may observe that Eq. (17) still describes a problem that can be solved using a least squares approach. The only difference is that instead of J+2 unknowns there are now J+K unknowns. This means that more equations are needed than in the first embodiment presented herein to get a good least squares solution, which generally is not a problem in a number of contexts, including an WCDMA/HSPA scenario with a dispersive channel.
or other channel estimation technique) (Step 120). Processing continues with initializing the code index k=0 (Step 122), and estimating the data correlation matrix corresponding to code k using, for example, Eq. (13) (Step 124). Processing continues with forming the corresponding least squares problem Cky=tk from Eq. (17) (Step 126). Here y=[γ0 0, γ1 0, . . . , γK-1 0, N0]T. Processing continues with incrementing the code index k=k+1 (Step 128), and determining whether k equals K (Step 130).
Carrying out Eq. (18) yields [γ0 0, γ1 0, . . . , γK-1 0, N0]T, representing the vector of channel code powers γ for the codes of interest and the corresponding noise variance (Step 134). While not illustrated, processing also may include dividing γk 0 by K∀k. As the elements in y are purely real, each complex-valued equation is treated as two real equations (equating real and imaginary parts) in the fitting process. Some equations may be omitted, such as the off-diagonal equations. Thus, fitting matrices may involve fitting a subset of elements.
Claims (24)
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